Estimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies
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2013Type
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This paper proposes a hybrid Newton-Raphson and genetic algorithm for the estimation of double cage induction motor parameters from commonly available manufacturer data. The hybrid algorithm was tested on a large data set of 6,380 IEC and NEMA motors and then compared with a baseline Newton-Raphson algorithm. The simulation results show that while the proposed hybrid algorithm is more computationally intensive, it does make significant improvements to convergence and error rates.
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Susanto, Julius and Islam, Syed. 2013. Estimation of Induction Motor Parameters Using Hybrid Algorithms for Power System Dynamic Studies, in Negnevitsky, M. (ed), Proceedings of the Australasian Universities Power Engineering Conference (AUPEC), Sep 29-Oct 3 2013. Hobart, Tasmania: University of Tasmania.
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Proceedings of the 2013 Australasian Universities Power Engineering Conference
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